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End date: 2021 × Start date: 2021 × End date: 2024 × Start date: 2020 × DDC: 690 × WGL Institute: PIK ×

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Now showing 1 - 4 of 4
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    Correlated power time series of individual wind turbines: A data driven model approach
    (Woodbury, NY : American Inst. of Physics, 2020) Braun, Tobias; Waechter, Matthias; Peinke, Joachim; Guhr, Thomas
    Wind farms can be regarded as complex systems that are, on the one hand, coupled to the nonlinear, stochastic characteristics of weather and, on the other hand, strongly influenced by supervisory control mechanisms. One crucial problem in this context today is the predictability of wind energy as an intermittent renewable resource with additional non-stationary nature. In this context, we analyze the power time series measured in an offshore wind farm for a total period of one year with a time resolution of 10 min. Applying detrended fluctuation analysis, we characterize the autocorrelation of power time series and find a Hurst exponent in the persistent regime with crossover behavior. To enrich the modeling perspective of complex large wind energy systems, we develop a stochastic reduced-form model of power time series. The observed transitions between two dominating power generation phases are reflected by a bistable deterministic component, while correlated stochastic fluctuations account for the identified persistence. The model succeeds to qualitatively reproduce several empirical characteristics such as the autocorrelation function and the bimodal probability density function. © 2020 Author(s).
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    Physico-chemical and bacteriological quality of groundwater in a rural area of Western Niger: A case study of Bonkoukou
    (London : IWA Publishing, 2020) Adamou, Hassane; Ibrahim, Boubacar; Salack, Seyni; Adamou, Rabani; Sanfo, Safietou; Liersch, Stefan
    The precariousness of the rural population in Africa is often symbolized by the lack of potable and safe drinking water. This study investigates the physico-chemical and bacteriological characteristics of 32 water samples with respect to WHO standards. The water samples were collected from wells, boreholes and small drinking water supply systems (DWS) in and around the township of Bonkoukou (Niger). The Water Quality Index (WQI) tool was used to assess the overall water quality with different physico-chemical parameters. Where the pH of the samples was acceptable, the samples showed higher levels of mineralization and deoxygenation. Overall, the samples were slightly hard, chlorinated and sulfated but much alkaline and contained nitrate and nitrite ions 2-16 times higher than the WHO standards. The use of WQI shows that samples in the DWS are safe for drinking. Samples coming from wells are the most polluted (58.50%) compared to those taken from boreholes (53.00%), while the percentage of samples from boreholes, unfit for drinking, is higher (41.00%) than that of the samples taken from wells (25.00%). Moreover, water in this area was characterized by the presence of total germs indicating bacteriological pollution. Hence, for the supply of safe drinking water to the larger number of people in such a rural area, the capacity of actual DWS must be improved and widespread. © 2020 The Authors.
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    Revisiting economic burdens of malaria in the face of climate change: a conceptual analysis for Ethiopia
    (Bradford : Emerald, 2020) Yalew, Amsalu Woldie
    Purpose: Climate change affects the geographic and seasonal range of malaria incidence, especially, in poor tropical countries. This paper aims to attempt to conceptualize the potential economic repercussions of such effects with its focus on Ethiopia. Design/methodology/approach: The paper is conceptual and descriptive in its design. It first reviews existing literature and evidence on the economic burdens of malaria, and the impacts of climate change on malaria disease. It then draws the economic implications of the expected malaria risk under the future climate. This is accompanied by a discussion on a set of methods that can be used to quantify the economic effects of malaria with or without climate change. Findings: A review of available evidence shows that climate change is likely to increase the geographic and seasonal range of malaria incidence in Ethiopia. The economic consequences of even a marginal increase in malaria risk will be substantial as one considers the projected impacts of climate change through other channels, the current population exposed to malaria risk and the country’s health system, economic structure and level of investment. The potential effects have the potency to require more household and public spending for health, to perpetuate poverty and inequality and to strain agricultural and regional development. Originality/value: This paper sheds light on the economic implications of climate change impacts on malaria, particularly, in Agrarian countries laying in the tropics. It illustrates how such impacts will interact with other impact channels of climate change, and thus evolve to influence the macro-economy. The paper also proposes a set of methods that can be used to quantify the potential economic effects of malaria. The paper seeks to stimulate future research on this important topic which rather has been neglected. © 2020, Amsalu Woldie Yalew.
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    First process-based simulations of climate change impacts on global tea production indicate large effects in the World’s major producer countries
    (Bristol : IOP Publ., 2020) Beringer, Tim; Kulak, Michal; Müller, Christoph; Schaphoff, Sibyll; Jans, Yvonne
    Modeling of climate change impacts have mainly been focused on a small number of annual staple crops that provide most of the world's calories. Crop models typically do not represent perennial crops despite their high economic, nutritional, or cultural value. Here we assess climate change impacts on global tea production, chosen because of its high importance in culture and livelihoods of people around the world. We extended the dynamic global vegetation model with managed land, LPJmL4, global crop model to simulate the cultivation of tea plants. Simulated tea yields were validated and found in good agreement with historical observations as well as experiments on the effects of increasing CO2 concentrations. We then projected yields into the future under a range of climate scenarios from the Inter-Sectoral Impact Model Intercomparison Project. Under current irrigation levels and lowest climate change scenarios, tea yields are expected to decrease in major producing countries. In most climate scenarios, we project that tea yields are set to increase in China, India, and Vietnam. However, yield losses are expected to affect Kenya, Indonesia, and Sri Lanka. If abundant water supply and full irrigation is assumed for all tea cultivation areas, yields are projected to increase in all regions.